Fast forward to the era of artificial intelligence; AI is one of the most talked about technologies of the current generation and holds vast potential. AI-enabled chips and sophisticated algorithms are key to many great advancements in a wide range of industries. Many of those breakthroughs have been enabled by the latest EDA innovations. As the synergetic cycle rolls forward, we are leveraging the power of AI to create new applications that design chips faster and better.
That’s why we’re excited about the DSO.aiTM technology we announced earlier this year. It stands for “design space optimization AI,” representing one of the most challenging chip design processes in the entire development flow. Specifically, searching the vast combined space of design and silicon technology choices to identify optimal recipes for the Holy Grail of chip design: performance, power and area (PPA).
In a complex chip with tens of millions of gates targeting a 5-nanometer process, the design flow is a very large space of potential solutions, nearly incalculable in human terms. Floorplan exploration alone can encompass trillions of possibilities for design teams to experiment with. And there is never a single “right” answer signifying ultimate completion.
In this environment, traditional, manual, design space exploration (DSE) can take many months of effort to reach satisfactory closure, and is strewn with tedious error-prone tasks and frustrating trial-and-error re-do cycles. By consequence, the exploration of choices in typical chip design workflows tends to be limited, and designs are rarely pushed to their architectural limits for PPA. It is a huge search problem with hundreds of millions of dollars of investment on the line.
This is where recent advancements in AI-based search technology can offer exciting ideas. New AI techniques like reinforcement learning (RL) have taught AI to play complex games like Chess or Go; synthesize and optimize neural networks; and match computational workloads to different types of accelerators. What if we could teach AI to search for optimal design recipes by using today’s tools?